Reduced scan range abdominopelvic CT in patients with suspected acute appendicitis - impact on diagnostic accuracy and effective radiation dose

CAR/CETARS/CSAR Practice Guideline on Imaging the Adult Patient With Right Lower Quadrant Pain

In 2023, the Canadian Society of Abdominal Radiology (CSAR) and Canadian Emergency, Trauma, and Acute Care Radiology Society (CETARS) received Canadian Association of Radiologists (CAR) member feedback that there was an unmet educational need for guidance in the imaging investigation of right lower quadrant (RLQ) pain. Members requested specific guidance on how to handle controversial scenarios including which test to order when, specifics of imaging protocols, and managing pregnant patients who have RLQ pain-all from a Canadian perspective. After conducting an exhaustive literature review, the working group agreed that a Canadian-specific set of guidelines was warranted. The management recommendations presented in this guideline were discussed as a group to achieve expert consensus. As the workup for RLQ pain can vary considerably in the paediatric population, the scope of this paper was restricted to adults (18 years of age or older). Whenever possible, the best evidence was used to inform the clinical guidance, and where gaps existed, the guidelines reflect consensus among experts in the field. The result is a framework to aid in this process of managing patients with RLQ pain across various clinical scenarios while addressing current questions and controversies, particularly those most relevant to the Canadian healthcare system.

"Rule out appendicitis": a Canadian emergency radiology perspective on medicolegal risks, imaging pitfalls, and strategies to improve care

We provide a unique Canadian perspective on the medicolegal risks associated with imaging acute appendicitis, incorporating data requested from the Canadian Medical Protective Association (CMPA) on closed medicolegal cases over the past decade. We include a review of current clinical and imaging guidelines in the diagnosis and management of this common emergency room presentation. A case-based approach is implemented in this article to explore ways to mitigate potential errors in the diagnosis of acute appendicitis.

An Overview on the Alignment of Radiation Protection in Computed Tomography with Maqasid al-Shari'ah in the Context of al-Dharuriyat

The increasing utilisation of computed tomography (CT) in the medical field has raised a greater concern regarding the radiation-induced health effects as CT imposes high radiation risks on the exposed individual. Adherence to radiation protection measures in CT as endorsed by regulatory bodies; justification, optimisation and dose limit, is essential to minimise radiation risks. Islam values every human being and Maqasid al-Shari'ah helps to protect human beings through its sacred principles which aim to fulfil human beings' benefits (maslahah) and prevent mischief (mafsadah). Alignment of the concept of radiation protection in CT within the framework of al-Dharuriyat; protection of faith or religion (din), protection of life (nafs), protection of lineage (nasl), protection of intellect ('aql) and protection of property (mal) is essential. This strengthens the concept and practices of radiation protection in CT among radiology personnel, particularly Muslim radiographers. The alignment provides supplementary knowledge towards the integration of knowledge fields between Islamic worldview and radiation protection in medical imaging, particularly in CT. This paper is hoped to set a benchmark for future studies on the integration of knowledge between the Islamic worldview and radiation protection in medical imaging in terms of other classifications of Maqasid al-Shari'ah; al-Hajiyat and al-Tahsiniyat.

Development of deep learning-assisted overscan decision algorithm in low-dose chest CT: Application to lung cancer screening in Korean National CT accreditation program

We propose a deep learning-assisted overscan decision algorithm in chest low-dose computed tomography (LDCT) applicable to the lung cancer screening. The algorithm reflects the radiologists’ subjective evaluation criteria according to the Korea institute for accreditation of medical imaging (KIAMI) guidelines, where it judges whether a scan range is beyond landmarks’ criterion. The algorithm consists of three stages: deep learning-based landmark segmentation, rule-based logical operations, and overscan determination. A total of 210 cases from a single institution (internal data) and 50 cases from 47 institutions (external data) were utilized for performance evaluation. Area under the receiver operating characteristic (AUROC), accuracy, sensitivity, specificity, and Cohen’s kappa were used as evaluation metrics. Fisher’s exact test was performed to present statistical significance for the overscan detectability, and univariate logistic regression analyses were performed for validation. Furthermore, an excessive effective dose was estimated by employing the amount of overscan and the absorbed dose to effective dose conversion factor. The algorithm presented AUROC values of 0.976 (95% confidence interval [CI]: 0.925–0.987) and 0.997 (95% CI: 0.800–0.999) for internal and external dataset, respectively. All metrics showed average performance scores greater than 90% in each evaluation dataset. The AI-assisted overscan decision and the radiologist’s manual evaluation showed a statistically significance showing a p-value less than 0.001 in Fisher’s exact test. In the logistic regression analysis, demographics (age and sex), data source, CT vendor, and slice thickness showed no statistical significance on the algorithm (each p-value > 0.05). Furthermore, the estimated excessive effective doses were 0.02 ± 0.01 mSv and 0.03 ± 0.05 mSv for each dataset, not a concern within slight deviations from an acceptable scan range. We hope that our proposed overscan decision algorithm enables the retrospective scan range monitoring in LDCT for lung cancer screening program, and follows an as low as reasonably achievable (ALARA) principle.

Automatic scan range for dose-reduced multiphase CT imaging of the liver utilizing CNNs and Gaussian models

Multiphase CT scanning of the liver is performed for several clinical applications; however, radiation exposure from CT scanning poses a nontrivial cancer risk to the patients. The radiation dose may be reduced by determining the scan range of the subsequent scans by the location of the target of interest in the first scan phase. The purpose of this study is to present and assess an automatic method for determining the scan range for multiphase CT scans. Our strategy is to first apply a CNN-based method for detecting the liver in 2D slices, and to use a liver range search algorithm for detecting the liver range in the scout volume. The target liver scan range for subsequent scans can be obtained by adding safety margins achieved from Gaussian liver motion models to the scan range determined from the scout. Experiments were performed on 657 multiphase CT volumes obtained from multiple hospitals. The experiment shows that the proposed liver detection method can detect the liver in 223 out of a total of 224 3D volumes on average within one second, with mean intersection of union, wall distance and centroid distance of 85.5%, 5.7 mm and 9.7 mm, respectively. In addition, the performance of the proposed liver detection method is comparable to the best of the state-of-the-art 3D liver detectors in the liver detection accuracy while it requires less processing time. Furthermore, we apply the liver scan range generation method on the liver CT images acquired from radiofrequency ablation and Y-90 transarterial radioembolization (selective internal radiation therapy) interventions of 46 patients from two hospitals. The result shows that the automatic scan range generation can significantly reduce the effective radiation dose by an average of 14.5% (2.56 mSv) compared to manual performance by the radiographer from Y-90 transarterial radioembolization, while no statistically significant difference in performance was found with the CT images from intra RFA intervention (p = 0.81). Finally, three radiologists assess both the original and the range-reduced images for evaluating the effect of the range reduction method on their clinical decisions. We conclude that the automatic liver scan range generation method is able to reduce excess radiation compared to the manual performance with a high accuracy and without penalizing the clinical decision.

Deep learning-based fully automated Z-axis coverage range definition from scout scans to eliminate overscanning in chest CT imaging

BACKGROUND

Despite the prevalence of chest CT in the clinic, concerns about unoptimized protocols delivering high radiation doses to patients still remain. This study aimed to assess the additional radiation dose associated with overscanning in chest CT and to develop an automated deep learning-assisted scan range selection technique to reduce radiation dose to patients.

RESULTS

A significant overscanning range (31 ± 24) mm was observed in clinical setting for over 95% of the cases. The average Dice coefficient for lung segmentation was 0.96 and 0.97 for anterior-posterior (AP) and lateral projections, respectively. By considering the exact lung coverage as the ground truth, and AP and lateral projections as input, The DL-based approach resulted in errors of 0.08 ± 1.46 and - 1.5 ± 4.1 mm in superior and inferior directions, respectively. In contrast, the error on external scout views was - 0.7 ± 4.08 and 0.01 ± 14.97 mm for superior and inferior directions, respectively.The ED reduction achieved by automated scan range selection was 21% in the test group. The evaluation of a large multi-centric chest CT dataset revealed unnecessary ED of more than 2 mSv per scan and 67% increase in the thyroid absorbed dose.

CONCLUSION

The proposed DL-based solution outperformed previous automatic methods with acceptable accuracy, even in complicated and challenging cases. The generizability of the model was demonstrated by fine-tuning the model on AP scout views and achieving acceptable results. The method can reduce the unoptimized dose to patients by exclunding unnecessary organs from field of view.

Diagnostic performance and radiation dose of reduced vs. standard scan range abdominopelvic CT for evaluation of appendicitis

OBJECTIVE

To compare the diagnostic performance and radiation dose of reduced vs. standard scan range CT in diagnosing appendicitis.

METHODS

We retrospectively evaluated 531 consecutive adults who underwent emergency contrast-enhanced CT for abdominal pain or suspected appendicitis between July 2018 and March 2019. One hundred eighty-one young adults (mean age, 26 ± 6 years) were imaged from L2 to the symphysis pubis (reduced protocol). A total of 350 older patients (mean age, 55 ± 17 years) and those with a wider differential diagnosis were imaged from the diaphragm to the ischium (standard protocol). The reference standard was histopathology (surgical cases) or 3 months of medical record follow-up (nonsurgical cases). Sensitivity, specificity, and accuracy were calculated. Mean dose-length products (DLP) were compared (t-test). Using an anthropomorphic phantom, organ doses were measured on CT scanners with (scanner 1) and without (scanner 2) automatic voltage selection; effective radiation doses were calculated.

RESULTS

The frequency of appendicitis was 57/181 (31.5%) and 80/350 (22.9%) in the reduced and standard groups, respectively. Results of the reduced and standard protocols respectively were as follows (95% CI in parentheses): sensitivity, 98.2% (90.4-99.9%) and 100.0 (95.3-100.0%); specificity, 99.2% (95.6-100.0%) and 99.6% (97.9-100.0%); accuracy, 97.8% and 97.4%; mean DLPs, 363 ± 191mGy∙cm and 633 ± 591mGy∙cm (p < 0.0001). Phantom-based measurements of effective dose were 47% lower on scanner 1 (4.64 vs. 2.48 mSv) and 26% lower on scanner 2 (4.68 vs. 3.45 mSv) with the reduced protocol.

CONCLUSION

For young adults with clinically suspected appendicitis, a reduced scan range CT protocol is as sensitive, specific, and accurate as a standard scan range CT and imparts significantly less radiation dose.

KEY POINTS

• A reduced scan range CT protocol in young adults with high suspicion of appendicitis demonstrates similar diagnostic performance as a full-range abdominopelvic CT in undifferentiated adult patients. • The reduced scan range CT protocol imparts significantly less radiation dose: 57% based on dose-length product data and 26-47% based on anthropomorphic phantom data.